Category Archives: Meteorology

Campbell Scientific (CSC) are an ISO 9001 certified company who are a leading manufacturer in a variety of applications related to weather, water, energy, gas flux and turbulence, infrastructure, and soil. Campbell Scientific, are committed to satisfying the instrumentation needs of their customers, and are internationally recognised in the measurement and control industry for producing accurate and dependable instruments

HC2A-S3

CSC systems are acclaimed for their dependability, which they demonstrate even in the most extreme weather climates. Their attributes include wide operating ranges, low energy usage, many communications options, and the flexibility to support a wide variety of measurement and control applications. Applications include, agriculture, air quality, fire warning, water quality, weather and climate recording, structural monitoring, Geo-technical monitoring and mining.

Rotronic and CSC have been business partners for many years, CSC uses the standard Rotronic meteo probe in many applications. Recently CSC installed the probe in a network of Road Weather Information Systems in Kelowna, British Columbia. CSC selected the probe because of its reliability, ease of use and accuracy. The HC2A-S3 is also highly regarded for its ability to function in extreme temperatures, this makes it good for the Canadian climate, and a perfect complement to Campbell Scientific systems.

” We value the Rotronic HC2A-S3 probe for its ability to function at extreme temperatures.” Mike Ryder Campbell Scientific, Canada

For more information on the latest HC2A-S click here ,or for any of our products please visit theRotronicwebsite.

For a long time, people have tried to predict weather conditions using the hydrologic climate cycle.In the early 1920’s scientists were able to compile a six hour forecast, back then it took six weeks to analyse weather data collected at only two points in Europe and calculate, by hand, a useful illustrative model. Today, supercomputers are used to predict the weather for a period of several weeks. The complex modelling programs require several million data points for parameters such as temperature, humidity, pressure, vertical & horizontal wind velocity with time stamps and absolute coordinates. To create a correlation between the data and the environment, scientists “slice” the atmosphere virtually into smaller horizontal &vertical parts—this process is called discretisation. It is more useful to compute the chronological change of the parameters using this model.

Clockwise from top left: Map of the average temperature over 30 years. .Weather station on Mount Vesuvius. .Water cycle summary

Meteorological events that are too “small” such as a single thunderhead, layer clouds or smaller turbulence’s will be parameterised through variables. This parameterisation is a science of its own that aims to reduce uncertainties as best as possible. Every forecast calculation starts with the current weather conditions. The quality of this input is crucial for the accuracy of the final forecast. Meteorologists link the forecast of yesterday’s weather with the actual measured parameters. Only large data centres are capable of computing this data assimilation. The overall result is a best possible calculation basis predict the weather for the next day. If this groundwork is flawed the forecast may be incorrect. For example, it could report rain at the wrong location. Today’s meteorological mathematicians also take parameters into account that change extremely slowly compared to the other factors. Growth and the reduction of polar ice, or the temperature of the oceans are summarised as boundary values. After a model is run using all the available data, meteorologists process and customise reports for a wide range of target groups such as public authorities, flight control centres, energy producers, industries and many more. These reports also include specific weather warnings.

Why the need to measure humidity?

Atmosphere composition diagram

As described above, the daily weather forecast relies on the precise measurement of weather parameters. The science of numerical weather prediction aims to describe the daily hydrologic cycle in numbers. Humidity plays an important role. Typically, data errors will multiply during calculations. Humidity values influence weather calculations e.g. through the water vapour balance equation— this formula expresses the influence of humidity through rain & condensation, and vice versa. Incorrect measurement or incomplete humidity data directly leads to wrong predictions of a huge number of weather phenomena such as the condensation altitude of clouds, locations of hyetal regions, fog layers and storms. In 1999, incorrect data sent by a weather station in Nova Scotia, Canada led to a incorrect forecast for Hurricane Lothar two days before it hit Central Europe. Authorities were insufficiently prepared to alert people in time. The prediction of rain and snowfall is still challenging for meteorologists. Only more extensive networks of weather stations and enhanced mathematical models will reduce problems due to unknown factors.

Facts & Figures

7 inches is the diameter of the largest hailstone ever recorded.

Sukkur City in Pakistan is one of the most humid places in the world with
30 °C dew point & a felt air temperature of 65 °C.

A study showed that a small thunderstorm system holds more than 10 million tons of water.

No two weather patterns are completely alike.

Some weather models assimilate data obtained from more than 25,000 weather stations.

We are pleased to announce our latest training course schedule for 2016. Courses include in partnership with Dave Ayres from Benrhos Ltd our practical 3 day temperature, humidity and dew point calibration and measurement uncertainty courses. In addition, for those seeking greater depth we are running dedicated courses on measurement uncertainty and ISO 17025 run by Lawrie Cronin and Dave Ayres

Its been pretty windy recently, So wind farms are probably doing quite well at the moment. The biggest wind farm in the world, at the moment, is the London array, which can produce 630MW of power.

Wind Energy in General

The future is very encouraging for wind power. The technology is growing exponentially due to the current power crisis and the ongoing discussions about nuclear power plants. Wind turbines are becoming more efficient and are able to produce increased electricity capacity given the same factors.

Facts & figures:

There is over 200 GW (Giga Watts) of installed wind energy capacity in the world.

The Global Wind Energy Council (GWEC) has forecasted a global capacity of 2,300 GW by 2030. This will cover up to 22% of the global power consumption.

Converting wind power into electrical power:

A wind turbine converts the kinetic energy of wind into rotational mechanical energy. This energy is directly converted, by a generator, into electrical energy. Large wind turbines typically have a generator installed on top of the tower. Commonly, there is also a gear box to adapt the speed. Various sensors for wind speed, humidity and temperature measurement are placed inside and outside to monitor the climate. A controller unit analyses the data and adjusts the yaw and pitch drives to the correct positions.

The formula for wind power density:

W = d x A^2 x V^3 x C

d: defines the density of the air. Typically it’s 1.225 Kg/m3. This is a value which can vary depending on air pressure, temperature and humidity.

A^2: defines the diameter of the turbine blades. This value is quite effective with its squared relationship. The larger a wind turbine is the more energy can be harnessed.

V^3: defines the velocity of the wind. The wind speed is the most effective value with its cubed relationship. In reality, the wind is never the same speed and a wind turbine is only efficient at certain wind speeds. Usually 10 mph (16 km/h) or greater is most effective. At high wind speed the wind turbine can break. The efficiency is therefore held to a constant of around 10 mph.

C: defines the constant which is normally 0.5 for metric values. This is actually a combination of two or more constants depending on the specific variables and the system of units that is used.

Why the need to measure the local climate?

To forecast the power of the wind over a few hours or days is not an easy task.

Wind farms can extend over miles of land or offshore areas where the climate and the wind speed can vary substantially,
especially in hilly areas. Positioning towers only slightly to the left or right can make a significant difference because the wind velocity can be increased due to the topography. Therefore, wind mapping has to be performed in order to determine if a location is correct for the wind farm. Such wind maps are usually done with Doppler radars which are equipped with stationary temperature and humidity sensors. These sensors improve the overall accuracy.

Once wind mapping has been carried out over different seasons, wind turbine positions can be determined. Each turbine will be equipped with sensors for wind direction, speed, temperature and humidity. All of these parameters, the turbine characteristics plus the weather forecast, can be used to make a prediction of the power of the turbine using complex mathematics.

There is a small weather station on the top of this wind turbine

The final power value will be calculated in “watts” which will be supplied into power grids. Electricity for many houses or factories can be powered by this green energy.

Why the need to measure inside a wind turbine?

Wind farms are normally installed in areas with harsh environments where strong winds are common. Salty air, high humidity and condensation are daily issues for wind turbines.

Normal ventilation is not sufficient to ensure continuous operation. The inside climate has to be monitored and dehumidified by desiccant to protect the electrical components against short circuits and the machinery against corrosion.

Internal measurements are required to ensure continuous operation and reduce maintenance costs of a wind farm.

The Calculation of Weather Data

What is the weather going to be like tomorrow?

For a long time, people have tried to predict weather conditions using the hydrologic climate cycle.

In the early 1920`s scientists were able to compile a six-hour forecast. Back then it took six weeks to calculate by hand the weather data collected at two points in Europe and create a useful illustrative model.

Today, supercomputers are used to predict the weather for a period of several weeks. The complex modelling programs require several million data points for parameters such as temperature, humidity, pressure, vertical & horizontal wind velocity with time stamps and absolute coordinates. To create a correlation between the data and the environment, scientists “slice” the atmosphere virtually into smaller horizontal & vertical parts – this process is called discretization. It is more useful to compute the chronological change of the parameters using this model.

Meteorological events that are too “small” such as a single thunderhead, layer clouds or smaller turbulences will be parameterised through variables. This parameterisation is a science of its own that aims to reduce uncertainties as best as possible.

Every forecast calculation starts with the current weather conditions. The quality of this input is crucial for the accuracy of the final forecast. Meteorologists link the forecast of yesterday’s weather with the actual measured parameters. Only large data centres are capable of computing this data assimilation. The overall result is a best possible calculation basis to predict the weather for the next day. If this groundwork is flawed the forecast may be incorrect, for example it could report rain at the wrong location.

Today’s meteorological mathematicians also take parameters into account that change extremely slowly compared to the other factors. Growth and the reduction of polar ice, or the temperature of the oceans are summarised as boundary values

After a model is run using all the available data, meteorologists’ process and customize reports for a wide range of target groups such as public authorities, flight control centres, energy producers, industries and many more, including the issue of specific warnings.

Facts & figures:

17.8 cm is the diameter of the largest hailstone ever recorded.

Sukkur City in Pakistan is one of the most humid places in the world with 30 °C dew point & a felt air temperature of 65 °C.

A study showed that a small thunderstorm system holds more than 10 million tons of water.

No two weather patterns are completely alike.

Some weather models assimilates data obtained from more than 25,000 weather stations.

Why The need to Measure Humidity?

As described above, the daily weather fore-cast relies on the precise measurement of weather parameters. The science of numerical weather prediction aims to describe the daily hydro-logic cycle in numbers – humidity plays an important role in this – data errors will multiply during calculations.

Humidity values influence weather calculations e.g. through the water vapor balance equation – this formula expresses the influence of humidity through rain & condensation, and vice-versa.

Incorrect measurement or incomplete humidity data directly leads to wrong predictions of a huge number of weather phenomena; this can include the condensation altitude of clouds, locations of hyetal regions, fog layers and storms.

In 1999, incorrect data sent by a weather station in Nova Scotia, Canada led to an incorrect forecast for Hurricane Lothar two days before it hit Central Europe. Authorities were insufficiently prepared to alert people in time.

What is the Rotronic Solution?

Rotronic products are used in weather stations around the globe. They provide temperature & humidity data continuously with high accuracy even in demanding environments.

Rotronic manufactures a range of meteorological probes and weather shields to meet the standards required by meteorological organizations.